{"id":"W7127986793","doi":"10.1093/eurheartj/ehaf784.230","title":"DeepOxyMap: AI-driven feature mapping of oxygenation-sensitive CMR for cardiomyopathy classification","year":2025,"lang":"en","type":"article","venue":"European Heart Journal","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre","funders":"","keywords":"Pattern recognition (psychology); Convolutional neural network; Feature (linguistics); Preprocessor; Magnetic resonance imaging; Cardiomyopathy; Feature extraction; Deep learning","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007739991,0.001075199,0.0006296344,0.001021759,0.0002252887,0.0007247619,0.001185482,0.0008330048,0.002686302],"category_scores_gemma":[0.002023504,0.0002485529,0.0007451916,0.0005539884,0.0002090977,0.0005835501,0.0009808489,0.0008631525,0.0007554427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003747176,"about_ca_system_score_gemma":0.0006650311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002742463,"about_ca_topic_score_gemma":0.002911093,"domain_scores_codex":[0.9997495,0.00005996748,0.0000128963,0.00008842965,0.00004407196,0.00004516385],"domain_scores_gemma":[0.9996372,0.0001557882,0.00003421374,0.00005067556,0.00008257052,0.00003945067],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008054859,0.0005784339,0.0091129,0.0002801924,0.0002411874,0.0003572881,0.0001116214,0.1146967,0.02753444,0.002260293,0.03126004,0.8127614],"study_design_scores_gemma":[0.00003568349,0.000110386,0.002035364,0.0000203578,0.00002930416,0.00009971367,0.00001969356,0.9867274,0.005880588,0.002982766,0.00204007,0.00001865136],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2284834,0.004253199,0.7459905,0.001271666,0.000405677,0.0003184812,0.005106573,0.01066863,0.003501896],"genre_scores_gemma":[0.7798911,0.0008990463,0.2036132,0.0007290189,0.0003002482,0.0003899741,0.008947397,0.0003146208,0.004915461],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002742463,"threshold_uncertainty_score":0.008986533,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03307003194610613,"score_gpt":0.3136932276908817,"score_spread":0.2806231957447756,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}